Science in the 20th century has given us a microscopic understanding of the world, ranging from the atomic realm of matter over the biological model of life to the psychology of individual thought and behavior. An important endeavor in the 21st century will be to understand the complex emergent patterns that characterize interacting systems in the physical, biological, engineering and social sciences. The vision of the AU Network for Computer Modelling of Complex Interactions is to combine expertise from physics, engineering, economics, business, cognitive neuroscience, and evolutionary biology to develop novel approaches for the study of intelligent, dynamically evolving systems.
All participants are established researchers in their fields who share a common methodological approach: combining simulation, experimentation, and statistical modeling in the study of small and large scale interactions in complex systems. One example where we expect our interdisciplinary cooperation to lead to crucial advances is in agentbased modeling: whereas physicists typically try to optimize quantum-physical processes with unrealistically simple rules for the interaction between agents, social scientists face the opposite challenge of limiting the rationality of their agents. The network participants share the vision to bridge this gap by modeling realistic agents, in between the extremes of the very primitive and the completely rational.